Linked Coupled Cluster Monte Carlo

TL;DR

This paper introduces a stochastic coupled cluster method reformulated with a similarity transformed Hamiltonian, reducing computational costs and enabling larger, more complex systems to be studied more efficiently.

Contribution

The paper presents a new formulation of the stochastic coupled cluster method that improves wavefunction representation granularity, lowering the critical population needed for accurate sampling.

Findings

Reduced critical population for sampling accuracy

Lower computational cost for larger systems

Extended applicability to higher excitation levels

Abstract

We consider a new formulation of the stochastic coupled cluster method in terms of the similarity transformed Hamiltonian. We show that improvement in the granularity with which the wavefunction is represented results in a reduction in the critical population required to correctly sample the wavefunction for a range of systems and excitation levels and hence leads to a substantial reduction in the computational cost. This development has the potential to substantially extend the range of the method, enabling it to be used to treat larger systems with excitation levels not easily accessible with conventional deterministic methods.